{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Try out [`nbgather`](https://github.com/microsoft/gather) 🧽✨\n",
    "\n",
    "Let's say you open this notebook after taking a few days off. You wonder, *How did I make that scatter plot? Didn't I have a better version of it? And can I get clean this code without breaking things?*\n",
    "\n",
    "The problem is that the cells are out of order and code was overwritten.\n",
    "\n",
    "With [`nbgather`](https://github.com/microsoft/gather), you can answer these questions!\n",
    "\n",
    "1. Hover over the scatter plot and click `Gather`\n",
    "2. Lines with the <span style='background-color: #e1d5f3;'>purple background</span> were the ones used to create the chart.\n",
    "3. *To open a notebook with the ordered, cleaned up code...* Click \"Gather to Notebook\"<br/>\n",
    "4. *To view all previous versions of the scatter plot...* Click \"Gather to Version Browser\"\n",
    "\n",
    "You can gather code for any <span style='border-radius: 5px; background-color: #c6ddfa;'>variable</span> or <span style='border-radius: 5px; border: 2px solid #c6ddfa'>output</span> that was added to the notebook after `nbgather` was installed. Try it by producing defining some variables and displaying some results.\n",
    "\n",
    "Learn more about these tools and leave feedback at the [nbgather site](https://github.com/microsoft/gather)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "execution_event_id": "c4985a2d-9e70-4106-b702-3f7e53586487",
    "last_executed_text": "kmeans = KMeans(n_clusters=4)\nclusters = kmeans.fit(data).labels_",
    "persistent_id": "442781fd-25c8-4da2-9d85-b2d19baee731"
   },
   "outputs": [],
   "source": [
    "kmeans = KMeans(n_clusters=4)\n",
    "clusters = kmeans.fit(data).labels_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "execution_event_id": "7d0d872d-89bc-46aa-b0e4-a08311cd9eb1",
    "last_executed_text": "scatter(petal_length, petal_width, c=clusters)",
    "persistent_id": "ee61160c-4a7e-4f0a-98d4-5154a399d907"
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x11e5cdb38>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "scatter(petal_length, petal_width, c=clusters)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "execution_event_id": "171ebc7f-f9ae-4ef7-b764-17376e4997a8",
    "last_executed_text": "from matplotlib.pyplot import scatter\nfrom sklearn.cluster import KMeans\nfrom sklearn import datasets",
    "persistent_id": "3d9b94c6-a842-4fae-a205-77619555983d"
   },
   "outputs": [],
   "source": [
    "from matplotlib.pyplot import scatter\n",
    "from sklearn.cluster import KMeans\n",
    "from sklearn import datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "execution_event_id": "cc482714-5153-4e1e-83eb-e7282b0db553",
    "last_executed_text": "data = datasets.load_iris().data[:,2:4]\npetal_length, petal_width = data[:,0], data[:,1]",
    "persistent_id": "d1a30223-b455-425e-a15b-3d92e9eb2293"
   },
   "outputs": [],
   "source": [
    "data = datasets.load_iris().data[:,2:4]\n",
    "petal_length, petal_width = data[:,0], data[:,1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "execution_event_id": "15fe80e2-d94d-4f38-861e-8fe9c391d494",
    "last_executed_text": "petal_length, petal_width = data[:,1], data[:,0]",
    "persistent_id": "430f94e6-ae2f-4574-9e3e-9bbc0bd4ff12"
   },
   "outputs": [],
   "source": [
    "petal_length, petal_width = data[:,1], data[:,0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "execution_event_id": "a048a4d5-e974-4312-872f-5145afbfc06f",
    "last_executed_text": "print(\"Average petal length: %.3f\" % (sum(petal_length) / len(petal_length),))",
    "persistent_id": "1e411882-dd5a-4822-9c1c-c363231df92b"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average petal length: 3.758\n"
     ]
    }
   ],
   "source": [
    "print(\"Average petal length: %.3f\" % (sum(petal_length) / len(petal_length),))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "persistent_id": "99d7df47-e3f1-47d6-8e65-c6078236e3e0"
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "history": [
   {
    "cell": {
     "executionCount": 1,
     "executionEventId": "171ebc7f-f9ae-4ef7-b764-17376e4997a8",
     "hasError": false,
     "id": "1f0e51c4-cbef-4211-bf78-08407c3c2121",
     "outputs": [],
     "persistentId": "3d9b94c6-a842-4fae-a205-77619555983d",
     "text": "from matplotlib.pyplot import scatter\nfrom sklearn.cluster import KMeans\nfrom sklearn import datasets"
    },
    "executionTime": "2020-01-16T15:52:28.954Z"
   },
   {
    "cell": {
     "executionCount": 2,
     "executionEventId": "cc482714-5153-4e1e-83eb-e7282b0db553",
     "hasError": false,
     "id": "f6001dd8-ca5e-4258-aad1-3c8f37d5348e",
     "outputs": [],
     "persistentId": "d1a30223-b455-425e-a15b-3d92e9eb2293",
     "text": "data = datasets.load_iris().data[:,2:4]\npetal_length, petal_width = data[:,0], data[:,1]"
    },
    "executionTime": "2020-01-16T15:52:31.464Z"
   },
   {
    "cell": {
     "executionCount": 3,
     "executionEventId": "a048a4d5-e974-4312-872f-5145afbfc06f",
     "hasError": false,
     "id": "3be1a3a1-4f9c-46a7-8472-f286fd9e1c0a",
     "outputs": [
      {
       "name": "stdout",
       "output_type": "stream",
       "text": "Average petal length: 3.758\n"
      }
     ],
     "persistentId": "1e411882-dd5a-4822-9c1c-c363231df92b",
     "text": "print(\"Average petal length: %.3f\" % (sum(petal_length) / len(petal_length),))"
    },
    "executionTime": "2020-01-16T15:52:35.045Z"
   },
   {
    "cell": {
     "executionCount": 4,
     "executionEventId": "4f54e0b0-2228-481b-8ec0-bfb4648287bb",
     "hasError": false,
     "id": "c2a58f27-88d2-473d-80d8-88876cf078ac",
     "outputs": [],
     "persistentId": "442781fd-25c8-4da2-9d85-b2d19baee731",
     "text": "kmeans = KMeans(n_clusters=4)\nclusters = kmeans.fit(data).labels_"
    },
    "executionTime": "2020-01-16T15:52:39.779Z"
   },
   {
    "cell": {
     "executionCount": 5,
     "executionEventId": "b3fcee27-7111-48e1-87ce-99adcaa06003",
     "hasError": false,
     "id": "46061077-a015-407d-934a-43982035004f",
     "outputs": [
      {
       "data": {
        "text/plain": "<matplotlib.collections.PathCollection at 0x11e1f3cc0>"
       },
       "execution_count": 5,
       "metadata": {},
       "output_type": "execute_result"
      },
      {
       "data": {
        "image/png": 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\n",
        "text/plain": "<Figure size 432x288 with 1 Axes>"
       },
       "metadata": {
        "needs_background": "light"
       },
       "output_type": "display_data"
      }
     ],
     "persistentId": "ee61160c-4a7e-4f0a-98d4-5154a399d907",
     "text": "scatter(petal_length, petal_width, c=clusters)"
    },
    "executionTime": "2020-01-16T15:52:44.378Z"
   },
   {
    "cell": {
     "executionCount": 6,
     "executionEventId": "e699ca1b-68bc-4889-8b31-ba31f0714bfb",
     "hasError": false,
     "id": "c2a58f27-88d2-473d-80d8-88876cf078ac",
     "outputs": [],
     "persistentId": "442781fd-25c8-4da2-9d85-b2d19baee731",
     "text": "kmeans = KMeans(n_clusters=5)\nclusters = kmeans.fit(data).labels_"
    },
    "executionTime": "2020-01-16T15:52:51.193Z"
   },
   {
    "cell": {
     "executionCount": 7,
     "executionEventId": "33a66ed4-dd3e-4468-a629-ce57db88e897",
     "hasError": false,
     "id": "c2a58f27-88d2-473d-80d8-88876cf078ac",
     "outputs": [],
     "persistentId": "442781fd-25c8-4da2-9d85-b2d19baee731",
     "text": "kmeans = KMeans(n_clusters=3)\nclusters = kmeans.fit(data).labels_"
    },
    "executionTime": "2020-01-16T15:52:56.603Z"
   },
   {
    "cell": {
     "executionCount": 8,
     "executionEventId": "228015b0-e3a9-4a86-8bb8-eaa783959c38",
     "hasError": false,
     "id": "c2a58f27-88d2-473d-80d8-88876cf078ac",
     "outputs": [],
     "persistentId": "442781fd-25c8-4da2-9d85-b2d19baee731",
     "text": "kmeans = KMeans(n_clusters=5)\nclusters = kmeans.fit(data).labels_"
    },
    "executionTime": "2020-01-16T15:53:01.731Z"
   },
   {
    "cell": {
     "executionCount": 9,
     "executionEventId": "fdfc72cf-a7fd-4490-a2b9-ad3cbc15d0b7",
     "hasError": false,
     "id": "46061077-a015-407d-934a-43982035004f",
     "outputs": [
      {
       "data": {
        "text/plain": "<matplotlib.collections.PathCollection at 0x11e3f74a8>"
       },
       "execution_count": 9,
       "metadata": {},
       "output_type": "execute_result"
      },
      {
       "data": {
        "image/png": 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\n",
        "text/plain": "<Figure size 432x288 with 1 Axes>"
       },
       "metadata": {
        "needs_background": "light"
       },
       "output_type": "display_data"
      }
     ],
     "persistentId": "ee61160c-4a7e-4f0a-98d4-5154a399d907",
     "text": "scatter(petal_length, petal_width, c=clusters)"
    },
    "executionTime": "2020-01-16T15:53:05.049Z"
   },
   {
    "cell": {
     "executionCount": 10,
     "executionEventId": "c02464d8-0e84-4690-9ff0-1d414f8c14da",
     "hasError": false,
     "id": "c2a58f27-88d2-473d-80d8-88876cf078ac",
     "outputs": [],
     "persistentId": "442781fd-25c8-4da2-9d85-b2d19baee731",
     "text": "kmeans = KMeans(n_clusters=3)\nclusters = kmeans.fit(data).labels_"
    },
    "executionTime": "2020-01-16T15:53:09.306Z"
   },
   {
    "cell": {
     "executionCount": 11,
     "executionEventId": "828533f0-9d19-4d5c-a8f9-9c0722caedc1",
     "hasError": false,
     "id": "46061077-a015-407d-934a-43982035004f",
     "outputs": [
      {
       "data": {
        "text/plain": "<matplotlib.collections.PathCollection at 0x11e240f60>"
       },
       "execution_count": null,
       "metadata": {},
       "output_type": "execute_result"
      },
      {
       "data": {
        "image/png": 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\n",
        "text/plain": "<Figure size 432x288 with 1 Axes>"
       },
       "metadata": {
        "needs_background": "light"
       },
       "output_type": "display_data"
      }
     ],
     "persistentId": "ee61160c-4a7e-4f0a-98d4-5154a399d907",
     "text": "scatter(petal_length, petal_width, c=clusters)"
    },
    "executionTime": "2020-01-16T15:53:10.016Z"
   },
   {
    "cell": {
     "executionCount": 12,
     "executionEventId": "296d956a-dd10-4b02-814a-6ae235e65424",
     "hasError": false,
     "id": "c2a58f27-88d2-473d-80d8-88876cf078ac",
     "outputs": [],
     "persistentId": "442781fd-25c8-4da2-9d85-b2d19baee731",
     "text": "kmeans = KMeans(n_clusters=2)\nclusters = kmeans.fit(data).labels_"
    },
    "executionTime": "2020-01-16T15:53:22.119Z"
   },
   {
    "cell": {
     "executionCount": 13,
     "executionEventId": "1c615fcd-1f9b-4bb5-b4a4-c9b55049c1a9",
     "hasError": false,
     "id": "46061077-a015-407d-934a-43982035004f",
     "outputs": [
      {
       "data": {
        "text/plain": "<matplotlib.collections.PathCollection at 0x11e556550>"
       },
       "execution_count": 13,
       "metadata": {},
       "output_type": "execute_result"
      },
      {
       "data": {
        "image/png": 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\n",
        "text/plain": "<Figure size 432x288 with 1 Axes>"
       },
       "metadata": {
        "needs_background": "light"
       },
       "output_type": "display_data"
      }
     ],
     "persistentId": "ee61160c-4a7e-4f0a-98d4-5154a399d907",
     "text": "scatter(petal_length, petal_width, c=clusters)"
    },
    "executionTime": "2020-01-16T15:53:23.044Z"
   },
   {
    "cell": {
     "executionCount": 14,
     "executionEventId": "c4985a2d-9e70-4106-b702-3f7e53586487",
     "hasError": false,
     "id": "c2a58f27-88d2-473d-80d8-88876cf078ac",
     "outputs": [],
     "persistentId": "442781fd-25c8-4da2-9d85-b2d19baee731",
     "text": "kmeans = KMeans(n_clusters=4)\nclusters = kmeans.fit(data).labels_"
    },
    "executionTime": "2020-01-16T15:53:30.284Z"
   },
   {
    "cell": {
     "executionCount": 15,
     "executionEventId": "7d0d872d-89bc-46aa-b0e4-a08311cd9eb1",
     "hasError": false,
     "id": "46061077-a015-407d-934a-43982035004f",
     "outputs": [
      {
       "data": {
        "text/plain": "<matplotlib.collections.PathCollection at 0x11e5cdb38>"
       },
       "execution_count": null,
       "metadata": {},
       "output_type": "execute_result"
      },
      {
       "data": {
        "image/png": 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\n",
        "text/plain": "<Figure size 432x288 with 1 Axes>"
       },
       "metadata": {
        "needs_background": "light"
       },
       "output_type": "display_data"
      }
     ],
     "persistentId": "ee61160c-4a7e-4f0a-98d4-5154a399d907",
     "text": "scatter(petal_length, petal_width, c=clusters)"
    },
    "executionTime": "2020-01-16T15:53:31.051Z"
   },
   {
    "cell": {
     "executionCount": 16,
     "executionEventId": "15fe80e2-d94d-4f38-861e-8fe9c391d494",
     "hasError": false,
     "id": "9cee9c52-640a-4a6f-97ac-0c7f301197fc",
     "outputs": [],
     "persistentId": "430f94e6-ae2f-4574-9e3e-9bbc0bd4ff12",
     "text": "petal_length, petal_width = data[:,1], data[:,0]"
    },
    "executionTime": "2020-01-16T15:53:40.921Z"
   }
  ],
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.6"
  },
  "uuid": "dc80cef4-ea23-4949-982e-beb74af18eef"
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
